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Eliminar la columna Cage manteniendo la compatibilidad con hojas de cálculo antiguas.

master
marcelcosta 11 months ago
parent
commit
092a788125
1 changed files with 17 additions and 15 deletions
  1. +17
    -15
      invivos/app.R

+ 17
- 15
invivos/app.R

@ -127,6 +127,11 @@ server <- function(input, output) {
table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6))) table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
} }
table$Volume<-as.numeric(table$Volume) table$Volume<-as.numeric(table$Volume)
if ("Cage" %in% colnames(table)){
table$Animal<-paste0(table$Cage, table$Animal)
table<-table[,-which(colnames(table) == "Cage")]
}
dades$taula<-table dades$taula<-table
dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = "Groups", colNames=F)[,1] dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = "Groups", colNames=F)[,1]
if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){ if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){
@ -252,7 +257,7 @@ server <- function(input, output) {
if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)}else{ if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)}else{
dades$taula %>% filter(DayPostInoc == input$day_vol) %>% add_column(sex="undefined")} %>% select(-Group), dades$taula %>% filter(DayPostInoc == input$day_vol) %>% add_column(sex="undefined")} %>% select(-Group),
df_def[,c("Animal", "group")] %>% unique, all=T, by="Animal") %>% rename(Group=group) df_def[,c("Animal", "group")] %>% unique, all=T, by="Animal") %>% rename(Group=group)
df_def<-select(df_def, Cage, Animal, Date, DayPostInoc, Group, Side, Weight, Long, Wide, Volume, Observations)
df_def<-select(df_def, Animal, Date, DayPostInoc, Group, Side, Weight, Long, Wide, Volume, Observations)
# if("DPV" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))} # if("DPV" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))}
# if("TS-Deep" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, `TS-Deep`,`TS-Length`,`TS-Width`, group))} # if("TS-Deep" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, `TS-Deep`,`TS-Length`,`TS-Width`, group))}
@ -326,7 +331,7 @@ server <- function(input, output) {
select(Animal, Group) %>% unique() select(Animal, Group) %>% unique()
dtemplate<-merge(dades$taula %>% select(-Group), template) %>% dtemplate<-merge(dades$taula %>% select(-Group), template) %>%
arrange(DayPostInoc, Animal, Side) %>% arrange(DayPostInoc, Animal, Side) %>%
select(Cage, Animal, Date, DayPostInoc, Group, Side,
select(Animal, Date, DayPostInoc, Group, Side,
Weight, Long, Wide, Volume, Observations) Weight, Long, Wide, Volume, Observations)
}else{ }else{
@ -343,6 +348,7 @@ server <- function(input, output) {
Volume="", Volume="",
Observations="" Observations=""
) )
template<-template %>% mutate(Animal=paste0(Cage,Animal)) %>% select(-Cage)
dtemplate<-template dtemplate<-template
} }
write.xlsx(list("Measures"=dtemplate, "Groups"=NULL,"Sex"=NULL), file) write.xlsx(list("Measures"=dtemplate, "Groups"=NULL,"Sex"=NULL), file)
@ -379,7 +385,10 @@ server <- function(input, output) {
table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6))) table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
} }
table$Volume<-as.numeric(table$Volume) table$Volume<-as.numeric(table$Volume)
table$Animal<-paste0(table$Cage, table$Animal)
if ("Cage" %in% colnames(table)){
table$Animal<-paste0(table$Cage, table$Animal)
table<-table[,-which(colnames(table) == "Cage")]
}
## Autocompletado de grupo ## Autocompletado de grupo
table_group<-merge( table_group<-merge(
@ -391,7 +400,6 @@ server <- function(input, output) {
table %>% select(-Group), table %>% select(-Group),
table_group table_group
) %>% relocate(Group, .after = DayPostInoc) %>% ) %>% relocate(Group, .after = DayPostInoc) %>%
relocate(Cage, .before = Animal) %>%
arrange(DayPostInoc, Animal, Side) arrange(DayPostInoc, Animal, Side)
if("Groups" %in% readxl::excel_sheets(input$file_analy$datapath)){ if("Groups" %in% readxl::excel_sheets(input$file_analy$datapath)){
@ -425,7 +433,7 @@ server <- function(input, output) {
table<-table %>% select(-Major, -Minor) %>% table<-table %>% select(-Major, -Minor) %>%
spread(Timepoint, Volume) %>% spread(Timepoint, Volume) %>%
mutate(across(all_of(timepoints), function(x){(x*100/`0`)-100})) %>% mutate(across(all_of(timepoints), function(x){(x*100/`0`)-100})) %>%
gather(Timepoint, Volume, -Cage, -`ID animal`, -`ID tumor`, -Group) %>%
gather(Timepoint, Volume, -`ID animal`, -`ID tumor`, -Group) %>%
mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume)) mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
} }
table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n) table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
@ -436,13 +444,11 @@ server <- function(input, output) {
observeEvent(analysis$taula, {}) observeEvent(analysis$taula, {})
table<-analysis$taula table<-analysis$taula
table$Animal<-paste0(table$Cage, table$Animal)
print(table) print(table)
animals<-unique(table$Animal) animals<-unique(table$Animal)
sides<-unique(table$Side) sides<-unique(table$Side)
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group) groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
basal<-data.frame( basal<-data.frame(
Cage="",
Animal=rep(animals, each=length(sides)), Animal=rep(animals, each=length(sides)),
Date="", Date="",
DayPostInoc=0, DayPostInoc=0,
@ -515,12 +521,10 @@ server <- function(input, output) {
observeEvent(analysis$taula, {}) observeEvent(analysis$taula, {})
table<-analysis$taula table<-analysis$taula
table$Animal<-paste0(table$Cage, table$Animal)
animals<-unique(table$Animal) animals<-unique(table$Animal)
sides<-unique(table$Side) sides<-unique(table$Side)
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group) groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
basal<-data.frame( basal<-data.frame(
Cage="",
Animal=rep(animals, each=length(sides)), Animal=rep(animals, each=length(sides)),
Date="", Date="",
DayPostInoc=0, DayPostInoc=0,
@ -608,8 +612,8 @@ server <- function(input, output) {
g<-list() g<-list()
for (side in c("L","R")){ for (side in c("L","R")){
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume)) tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
table_tumor<<-endtime table_tumor<<-endtime
g[side]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor), g[side]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
@ -676,7 +680,6 @@ server <- function(input, output) {
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume)) tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$DayPostInoc)) > 1){ if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$DayPostInoc)) > 1){
print(paste0("Side: ",side)) print(paste0("Side: ",side))
# print(summary(aov(Volume~Group+DayPostInoc+Error(paste0(Animal,Cage)), data=tableR)))
print(summary(aov(Volume~Group+DayPostInoc+Error(Animal), data=tableR))) print(summary(aov(Volume~Group+DayPostInoc+Error(Animal), data=tableR)))
} }
} }
@ -761,7 +764,6 @@ server <- function(input, output) {
sides<-unique(table$Side) sides<-unique(table$Side)
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group) groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
basal<-data.frame( basal<-data.frame(
Cage="",
Animal=rep(animals, each=length(sides)), Animal=rep(animals, each=length(sides)),
Date="", Date="",
DayPostInoc=0, DayPostInoc=0,
@ -951,8 +953,8 @@ server <- function(input, output) {
count<-1 count<-1
for (side in c("L","R")){ for (side in c("L","R")){
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume)) tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
table_tumor<-endtime table_tumor<-endtime
if (input$colors != ""){ if (input$colors != ""){
col<-strsplit(input$colors, ",")[[1]] col<-strsplit(input$colors, ",")[[1]]

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